{"id":"W2806632051","doi":"10.1182/bloodadvances.2017gs101973","title":"Development of research capacity in sickle cell anemia in Uganda: impact of collaborations","year":2017,"lang":"en","type":"article","venue":"Blood Advances","topic":"Hemoglobinopathies and Related Disorders","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Anemia; Sickle cell anemia; Medicine; Intensive care medicine; Immunology; Internal medicine; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04113047,0.0006699772,0.0006190732,0.003222663,0.003617699,0.008401064,0.003328325,0.002518839,0.02480474],"category_scores_gemma":[0.07886233,0.0006216867,0.0007900225,0.003438365,0.002349268,0.006768947,0.01697476,0.003126252,0.002938452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005037072,"about_ca_system_score_gemma":0.0670677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006986476,"about_ca_topic_score_gemma":0.007405997,"domain_scores_codex":[0.9481282,0.03914686,0.002485016,0.001706386,0.00306392,0.005469695],"domain_scores_gemma":[0.7992027,0.03421261,0.01761834,0.006775904,0.02565963,0.1165308],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001436111,0.001449682,0.2920418,0.006702782,0.0004985863,0.003592421,0.02088071,0.001185993,0.001562515,0.0382829,0.1484986,0.4838679],"study_design_scores_gemma":[0.001201763,0.002937312,0.2551458,0.02375615,0.0005047196,0.005223046,0.08022902,0.002316156,0.001610254,0.04086515,0.5858229,0.0003876065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3165072,0.08570214,0.006578787,0.4831687,0.008047894,0.001687029,0.004104744,0.0006198334,0.09358381],"genre_scores_gemma":[0.9059947,0.03396079,0.0194104,0.02297029,0.002857094,0.00157743,0.00162333,0.000152747,0.01145323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9588695,"threshold_uncertainty_score":0.2175213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0567489692581746,"score_gpt":0.3657060587780195,"score_spread":0.308957089519845,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}